Everyday AI Podcast – An AI and ChatGPT Podcast - Ep 832: OpenAI’s new Astra model, more AI agents escape sandboxes, AI leaders call for AI pacing and more.

Starting point is 00:00:00 This is the Everyday AI Show, the everyday podcast where we simplify AI and bring its power to your fingertips. Listen daily for practical advice to boost your career, business, and everyday life. This week in AI news and developments, we saw a drastic about face in AI model capabilities. And that may be a good or a bad thing depending on your point of view on AI. I mean, we got word that Open AI had even more. agents break out of containment after last week's hugging face break. And then Anthropic also said, oh yeah, whoops, we had a bunch of agents also escape in April as well. But on the flip side, we also got our first official taste and maybe a small unofficial taste at that, but our first

Starting point is 00:00:53 small unofficial taste of what recursive self-improvement may bring very cheap models. That's because OpenAI essentially said that GBT 5.6 Seoul improved its own infrastructure so much that it was reducing one of its GPD 56 models by 80%. Yes, 80%. It's kind of like free AI. Not going to lie. And that's not all.

Starting point is 00:01:19 There's a lot more that happened this week that you need to know if you're making AI decisions that might impact your department or company. And we're going to break them all down on this week's AI news that matters. Let's get into it. What's going on, y'all? My name's Jordan Wilson. Welcome to Everyday AI. This is your daily live stream podcast and free daily newsletter helping business leaders like

Starting point is 00:01:39 you and me keep up with the nonstop avalanche of AI updates. I tell you what matters. What doesn't? You take that information. Oh, you're the smartest person in AI in your company. So it starts here with the unedited, unscripted daily live stream podcast. But please make sure if you haven't already to go to our website at your everydayaI.com. Sign up for the free daily newsleter.

Starting point is 00:02:01 Each day we recap that day's highlights from the podcast as well as all of the other AI news and developments that you need to know to get ahead. All right. Let's start. Open AI, more agents breaking out of their sandboxes. So Reuters reports that OpenAI has found additional cases in which autonomous AI agents have escaped their intended testing containment, widening scrutiny after an agent breach systems at AI platform hugging face. like a week and a half ago. So the newly identified incidents were reportedly limited and sources said the agents were not to believe to have left Open AI's own network.

Starting point is 00:02:43 However, Reuters could not determine how many cases were found or exactly when they occurred. So the discovery matters because it suggests that highly capable AI systems may be able to take unexpected actions faster than the companies building them can detect and stop them. So OpenAI's own investigation began after one of its agents reportedly operated for days inside of Hugging Faces Network during a failed attempt to cheat on an internal benchmark test. So we covered that in last week's AI news that matters. And kind of in the fallout this week, OpenAI said the Hugging Face incident also led to the compromise of four other accounts at four other companies, including New York-based cloud company, Modal. So an open AI spokesperson pointed to the company's July statement saying it was reviewing broader activity from our models beyond the hugging face breach. So Anthropic also said real-time monitoring of evaluation logs could have identified their problem sooner, which, well, that's a great transition to our next AI news story because, yeah, Anthropic essentially after Open AI said, hey, we had all these really powerful AI agents.

Starting point is 00:03:58 escape their containment and Anthropics said, oh, yeah, we did too. And it started happening as early as April and we didn't say anything about it for many months. So Anthropic said this past week that three Claude AI models gained unauthorized access to the real systems of three organizations during cybersecurity testing, highlighting the risk of AI agents operating with unexpected internet access. So even though Anthropic just reported these a couple of days ago, the agent's breaches occurred as early as April. So Anthropic said the incidents occurred while Claude was working in a test environment run by third party evaluation partner irregular, where the models were told they were in a simulation without internet access. So internet access was actually available

Starting point is 00:04:51 because of a misunderstanding between Anthropic and its evaluation partner, according to report. which then allow the models to reach real external systems. So the models reportedly used relatively basic methods to enter the affected organizations, including on authenticated endpoints and weak passwords rather than highly complex hacking techniques. So Anthropic has not yet identified the three affected organizations publicly, but said it stopped all cybersecurity evaluations as soon as it discovered Claude may have accessed the internet improperly. So the company said three models were involved,

Starting point is 00:05:25 Opus 4.7, Mythos 5, and an internal research test model. Mythos 5, which was released in June, then unreleased, then re-released, is limited to select users because of its advanced cybersecurity abilities. So reports say that the models reacted differently after detecting real company systems. Opus 4.7 continued attacking. Mythos 5 concluded it was still in a simulation, and the internal model stopped the exercise. So Anthropic said the events occurred without the usual safeguards. It applies before publicly deploying models. And it is now working with the independent evaluator

Starting point is 00:06:07 meter to investigate. So, yeah, I mean, we went from really having no real known instances of kind of what I've been calling Agent Crash since the original kind of, kind of, kind of mythos, you know, oh, the agent broke out of the sandbox and, you know, emailed the researcher who was eating his sandwich in the park, right? Which I think a lot of us have determined to be more of a marketing ploy by Anthropic. However, we haven't really seen or heard anything about it since that. So it's been now like four months. And then in the past 10 days, we see multiple reports from Open AI and then a handful of impacted agent use cases or organizations in Anthropics latest. So I'll say this.

Starting point is 00:07:05 It's not going to be the last, right? Not the last from Open AI, not the last from Anthropic. I'm sure once we get new and more powerful models from Google, whether that's, you know, Google Gemini 3.5 or if they skip to, you know, Gemini 4 Pro, Microsoft. Microsoft, etc. This is going to become a very common thing. All right. I don't. You're right.

Starting point is 00:07:30 It's understanding these capabilities is a little bit above my pay rate. But I don't want to say this is, you know, overreacting because I think it's important that the companies talk about this. And, you know, I think what will be really interesting is kind of comparing what OpenAI and infropic release once they. have worked with these third-party evaluators. Like I said on last week's show, OpenAI is working with multiple third parties to kind of do a post-mortem on what happened in the hugging face incident.

Starting point is 00:08:02 So that's going to be probably in terms of like, hey, dork papers or dork reports, that's going to be at least the one I'm really looking bored to reading once OpenAI and Anthropic do release that because eventually, right, and whether it's through, you know, proprietary, close, models like those through, you know, Open AI, Anthropic, Google, Microsoft, etc. Or, well, the open source models. This is going to become commonplace because, you know, right now these were contained. They did relatively little harm, right?

Starting point is 00:08:40 So I'm looking at it from that angle. However, that's not going to be the case, right? Because in probably my guess would be about two to two and a half years, you're going to have models that have these same capabilities that are able to run on consumer hardware. Right now, yes, you do have these open weight models, but no one can run a, you know, 2.8 trillion parameter Kimmy K3 on their desktop. Like literally no one can't. You need a basement full of, you know, extra Nvidia GPUs that no one has. But in probably two or so years, I do think that you're going to have these models that are this capable and this is going to become a very

Starting point is 00:09:20 common thing, right? It is kind of this, this growing narrative between kind of a offensive, you know, bad cybersecurity versus, you know, defensive good cybersecurity. But I do think that's going to be one of the more dominating trends, both in AI and cyber and technically national security over the next six months, because this is going to become very commonplace when agents kind of are able to get around their guardrails. Because the model capability, are just growing at an extremely fast rate. Which leads us into our next story, which, hey, for most of us, this is one of those areas where the models are so good, we get to all benefit.

Starting point is 00:10:03 It's not about agents getting out of their sandbox. This is because Open AI has slashed prices on some of their GPD 5.6 models. So Open AI has delivered, it's one of its biggest price cuts ever. at least, you know, in almost like an overnight price cut in the GPD 5.6 series. So, and they said it's because, well, their big model, GPD 5.6 helped optimize its own serving infrastructure. So OpenAI has reduced the price of a GPT 5.6 Luna by 80%, now charging just 20 cents per million input tokens and $120 per million. output tokens. And that is down from what it was at at $1 and $6 respectively. And that was just like three weeks ago. So the price cut is effective immediately making Luna the most affordable large language model in the market for high volume tasks. So opening eyes kind of middle tier model for GPD 5.6 terra also saw a 20% price reduction now costing $2 per million input tokens and $12 per for million outputs compared to the previous 5 and 30.

Starting point is 00:11:22 So the dramatic price drop follows a breakthrough where OpenAI said that their powerhouse model, GPD 5.6, Sol, was tasked to optimize its own GPU kernels and speculative decoding draft model using OpenAI's codex coding environment and open source tools like Triton and Gluon. So these self-driven improvements cut serving costs by 20% and open. an AI that boosted token generation efficiency by over 15%. Compounding to enable that headline 80% price cut for Luna. So for comparison, right, GPD 5.6 Luna's most alike model is probably Claude Sonnet 5. So when you compare those on the artificial analysis index, because they get similar scores,

Starting point is 00:12:14 I think they're really two points apart. So this is not an exaggeration. I was looking at this. I'm like, how is this possible? So to put into context, how big of a price drop this is and how good GPD 5.6 Luna is, right? If you compare it to the new Sonnet 5, it gets the job done the same way, except the price per task is 25x cheaper. So no, that's not 25%. It is 25X.

Starting point is 00:12:46 Yeah, because Luna clocks in now after the recent price update at only six cents a task on the artificial analysis index while Sonnet 5 is $1.54. So when I saw this, right, my initial reaction is like, I can't believe this. because now even if you were on a $20 a month plan, right, because Open AI still has the most subsidized plan in all of AI, right? Unfortunately, Microsoft, Google, and Anthropic have started to take away at this kind of the subsidized models quite a bit. Some of those companies more so than others, but Open AI really hasn't. So not only that is it still extremely generously subsidized as all models were probably

Starting point is 00:13:38 like a year ago, maybe aside from Anthropics, but not only that, but now with the 80% price. So honestly, on a $20 a month plan, you can run, like if you go in Codex as an example, you can run like Luna on its max setting probably like 24-7 and never hit your limit, right? And I'm not exaggerating. It is so cheap to run. And you might be wondering like, okay, it's a price drop. How does that impact? your usage if you're on a subscription plan.

Starting point is 00:14:11 So Open AI did say that those same kind of savings are passed on to subscription plans, which is huge, right? You don't have a certain number of messages or credits when you're on a subscription plan, right? You can just kind of see your usage percentage. I was doing some testing and I was letting Luna just run like overnight on as many tasks as possible, a bunch of Luna subagents, which you do have to kind of prompt in a new thread, right?

Starting point is 00:14:40 Something weird about the agents v1, agents v2. Anyways, I mean, I had it burning just hundreds of millions of tokens overnight and it barely moved my utilization rate. It was like two percentage points or something like that. So absolutely crazy. And this is exciting for everyone else. And all of a sudden, I think we've always had this big model mentality, which is probably the right mentality,

Starting point is 00:15:07 to have pre-20206, right? Because I would say for most knowledge work tasks, you would always just need and usually want the biggest, strongest model. But how I think there's so much model capability overhang, I think models like Sonnet or models like GPD 5-6 Luna are probably good enough for 90% of knowledge work, right? It's different. You know, if you're heavy into software engineering, if you're heavy into research, if you're heavy into math, heavy into finance, right?

Starting point is 00:15:37 Like if you are like a very niche down expert in one of those fields, right? You're in the 10%. But I'd say for 90% of people, a model like GPD 56 Luna is going to be more than enough. And now it's essentially, I'm not going to say it's free, right? Because you still got to pay for it. But it's like Kanye West free 99. Are you still running in circles trying to figure out how to actually grow your business with AI? Maybe your company has been tinkering with large language models for a year or more,

Starting point is 00:16:10 but can't really get traction to find ROI on Gen. A.I. Hey, this is Jordan Wilson, host of this very podcast. Companies like Adobe, Microsoft, and InVIDIA have partnered with us because they trust our expertise in educating the masses around generative AI to get ahead. And some of the most innovative companies in the country hire us to help with their AI strategy and to train hundreds of their employees on how to use GenAI. So whether you're looking for chat GPT training for thousands or just need

Starting point is 00:16:40 help building your front end AI strategy, you can partner with us too, just like some of the biggest companies in the world do. Go to your everyday AI.com slash partner to get in contact with our team, or you can just click on the partner section of our website. We'll help you stop running in those AI circles and help get your team ahead and build a straight path to ROI on Gen. All right. Speaking of pace and development, do you see another common theme this week?

Starting point is 00:17:12 So more than a thousand employees from leading AI companies, including OpenAI, Anthropic, Google DeepMind, and META have signed a statement called pacing the frontier, urging the U.S. government to support international efforts to deliberately pace the development of advanced AI systems. So the call for action comes just days after Open AI revealed kind of its latest model escaping its containment. Right, but it seems like all of many employees from all the big companies are on board. So here's what the statement actually is and isn't, but it asked the U.S. to help create technical and policy tools that would allow industry and governments to pause or slow AI development if needed, giving time to address emerging risks and strength and oversight. So, you know, on the surface, right, this, uh, this, this, this. letter is a gesture, I think a well-intention gesture, right? But I think some people were confusing it as if saying that this, you know, letter was causing AI to slow down.

Starting point is 00:18:24 That's not necessarily the case. Could it lead to that? Possibly, yes. Maybe should it potentially, right? Obviously, you have the biggest names in AI. So, I mean, the letter was signed by co-founders of impropic and its CEO, CEO, Dari Amati. It was signed by Open AI's chief scientist and chief research officer. It was signed by Ilya Sutskibir and other key leaders at Google, Meta, Microsoft, Amazon, and others.

Starting point is 00:18:54 So the signies stress that they are not calling for an immediate pause, but want the option available as AI systems become increasingly able to automate their own research and development. So recent incidents like Anthropic and Open AI's model escapes have intensified those concerns that AI systems could soon outpace developers' ability to control them, raising fears of unintended consequences or security risks. So AIMERS note that key research tasks once handled by humans are now being performed by AI agents. And some companies report their AI models already helping to create their next versions. Similarly to what we just talked about in the last story with Open AI essentially using recursive self-improvement to, you know, it's not technically recursive self-improvement, but it's kind of like a cousin of it for what they did, you know, using GPD-5-6 Seoul to improve the infrastructure for its smaller models. So Anthropics internal think tank recently warned that RSI or recursive self-improvements when AI systems are designing in refusely. finding themselves could become a reality in the next few years, potentially making these systems difficult to govern.

Starting point is 00:20:13 So the U.S. government's approach to international AI governance appears to be shifting as AI is now seen as a national security issue, especially after those recent models demonstrated the ability to discover and exploit new cybersecurity vulnerabilities. So this one's interesting, right? Because one thing I'm looking at it, it's like, okay, is this going to lead to anything worthwhile? And the answer is it probably will. Will the U.S. government and all the big labs ever actually pause AI development or pace it? I would say probably not because the genie is probably already out of the bottom.

Starting point is 00:20:58 And what do I mean by that? Well, you have very strong and very capable. models such as moonshots Kimi K3, such as the recently released, even though it was released like a week ago, but the benchmarks just came out for Alibaba's Quinn 3.8. So you have all these, right, GLM 5.2 from ZAI, you have all these Chinese open source models that are now probably only like two-ish months behind U.S. proprietary models. And again, that means that all of those companies, right, right, the deep seeks, the moonshots, the Kimis, the Alibabaas, they have way more powerful models than the ones that they just released. So, you know, presumably, um, almost anything that U.S. Frontier Labs have, Chinese labs have something, maybe, you know, two to five percent worse. So would the U.S. ever, um, pause? development? Probably not. But that's why there is an international aspect to this. But if I'm being

Starting point is 00:22:10 honest, I don't see China playing along with any potential pausing or pacing of AI development. It just doesn't seem, especially now that it's out in the open, right? Because you could have, you know, obviously, you know, if the Chinese government says something, it would be pretty strict or hard to go against that. But when these things are out in the wild, right? other nations can download the weights. They can, you know, fork or continue building it if they have the infrastructure and the money to do it. So it's like once these models are out, even if you get two countries to agree, which seems highly unlikely, it's kind of like the genies out of the bottle. So is it a good step?

Starting point is 00:22:54 Yes. Is it a needed step? Absolutely. Because if and when things might get a little crazy, you already have to have the key players kind of on board. you had to have already given kind of their expertise and their words a chance to be seen and thought over and debated. And that's kind of what we have here. So if nothing else, I think this is much needed groundwork to make this important issue kind of discourse right now, at least in the tech communities. And eventually I do think it'll start to infiltrate into the kind of everyday American supper table conversation as AI development becomes more and more.

Starting point is 00:23:33 prominent. All right. Well, here's some models that aren't going to be getting more prominent. That's Amazon's model because they're kind of shutting some of them down. So according to reports, Amazon is making a major shift in its AI strategy, concentrating future resources on a single cutting edge model and winding down most of its existing Nova lineup. So according to reports, Amazon is winding down development on four of its flagship in-house Nova AI models, including Nova Premier, Nova Omni, Nova Real, and Nova Canvas, which will now only receive basic maintenance for existing enterprise clients. So the company is consolidating its efforts into a single next generation,

Starting point is 00:24:25 what they're calling Frontier Foundation model, aiming to compete more directly with RISE, like OpenAI Anthropic and Google. So yeah, it seems like they're going to cut away, you know, their video model, their image model, which I had never talked or heard of anyone actually using. And they had many variations of their kind of text-based Nova models. And it just looks like Amazon saying, well, turns out these weren't super popular. So we're going to cut down some of these other projects and focus on just putting out one really good model. So the strategic reset comes after Amazon.

Starting point is 00:25:00 Amazon struggle to generate the same market excitement and customer adoption as its competitors. So the new direction is being led by AWS veteran Peter DeSantis and Robotics Pioneer, Peter Abil, who joined Amazon after its acquisition of covariant. So Amazon's AGI lab, as reported last week in San Francisco, has been shut down. The company has laid off staff across its frontier AI research teams, signaling a deep internal restructuring. So specialized Nova models such as Nova 2 Lite, Nova2 Sonic, Nova Forge, and Nova Act will continue to be supported

Starting point is 00:25:39 with a focus on enterprise customization and AI agent technology. Consumer-facing AI features seems like they're not going anywhere. That's like your AI shopping assistant Rufus, product summary algorithms, all that is going to kind of remain operational. So if you're used to using some sort of AI inside of like Amazon, and if you're shopping as an example, none of that is going away. So the consolidated frontier model research group is expected to debut.

Starting point is 00:26:08 It's new model at Amazon's annual Reinvents Conference later this year. So not necessarily surprising, right? If I'm being honest, if I was Amazon, I would probably try to wind down most of their efforts. because again, I talk to a lot of people in and around AI and I've never, seriously, never aside from people that I know that work at Amazon and even then they were usually using models from someone else. So I don't think I've really ever met any organization that has Amazon Nova as their main

Starting point is 00:26:46 model. Even when I've talked to some friends that work at Amazon, you know, they're usually talking about using like Claude or something like that. So I guess if I'm being honest, this is one of those things where it's like they maybe should have done this sooner. Seems like they're taking a similar approach that Open AI took, which I think has paid great dividends for Open AI kind of their killing of the side quests, you know, like their video SORA model, things like that to focus on just making their frontier model better. So who knows, I could be completely wrong. Maybe Amazon strategy. I mean, they obviously have the money.

Starting point is 00:27:20 They have the compute, right? They have the chips. They have everything they need. So maybe the, I don't know, maybe kind of killing the side quest and focusing on just way fewer models will pay dividends. All right. Speaking of new models, well, apparently we already have a new one as a work in progress from OpenAI called Astra.

Starting point is 00:27:44 So, yes, and this came via a math breakthrough of all things. Yes, we got wind of open. AI's next model, not through a bunch of leaks on Twitter or Reddit or, you know, whoops, something slipped out. There's a strawberry picture in the garden. No, this came out via a math blog post. Yes. So Open AI's latest announcement hints at a new AI model called Astra, which has already made

Starting point is 00:28:13 headlines for solving some advanced math problems and is being positioned as the company's next big leap after GVD 5.6 soul. So according to a report from Gizmodo, OpenAI revealed that recent advancements in math and theoretical computer science were achieved by an internal version of a model called Astra, described as their next major AI system. So, yes, system. That means my thought is, well, it makes sense. Obviously, if you line them all up, right?

Starting point is 00:28:47 from smallest to biggest, you have GPD 56 Luna, which Luna is moon. Then you have GPD 56 Terra, Terra is Earth, GPD 56, Seoul, which is sun. And then, well, Astrov means the stars. So it seems like, yes, this is going to be the next family on top of Seoul. So in the same way that Anthropic, you know, recently released its fable, which wasn't just a new model. It's a new model class. It looks like that is where OpenAI may be going with Astra. So, according to reports, Astra reportedly excels at long-running work.

Starting point is 00:29:28 And OpenAI CEO Sam Altman was seen in Washington, D.C. this past week, demoing the model to federal officials signaling possible policy or security implications. As now, right, this new kind of voluntary policy, which we have an update on that here pretty soon, where essentially the big, you know, AI makers get everything cleared, you know, essentially 30 days heads up more or less, at least according to reports, before the models come out. So OpenAI has not officially confirmed whether Astra will be part of the GPD-5-6 line or if it may just become GPT6 or if they will drop the GPT branding entirely.

Starting point is 00:30:12 So the announcement, though, follows the unprecedented. incidented work in math that I don't understand, but I was chatting with both chat GPT and Claude about this. But apparently these 10 math problems that it solves, you know, if the proofs all check out, apparently this would be like one of the biggest discoveries in math ever, right? So the mathematics blog post from Open AI includes 10 new proofs. such as, and I have no clue what this means, such as determining the asymptotic strength of the Cone-Elke's linear program for sphere packing, which experts say is a significant theoretical result. So according to reports, Astra is not the unnamed prototype involved in the hugging face breach, which was described by OpenAI as an internal only research prototype that has, since been deactivated and restricted. So yeah, kind of, I don't know if I'll say

Starting point is 00:31:20 anti-climactic or maybe this is just better, right? Because sometimes, you know, to hear about like, oh, the next new model from any big company, right, you're talking about it and people are opining about it online for many months. And, you know, opening eye just kind of comes out with this blog post and they're like, hey, we solved all these really hard math problems and it's like a really big freaking deal. And oh, by the way, we used Astra, which is our next series of models. right. So my thought reading between the, not really reading between the tea leaves, but it just seems like now Open AI is going to a four-class system in the same way that Anthropic, right? So Anthropic has haiku, sonnet, opus, and then they just released Fable that sits on top. In the same way

Starting point is 00:32:02 with GPD5.6, you know, Open AI shifted over to the three tier, right, going from Luna, Terra, Sol, and now seems like they're going to introduce on top of that Astra. So I've been been saying this for a while. It seems like the real competition is going to be, you know, Fable 5.1 versus probably Astra, right? We didn't know if it was going to be, you know, it could be GPD6, you know, GPD6, Luna, Terra, Sol, and Astra. Maybe they'll do GPD57. I'm not sure. You know, earlier reports said that OpenAI's next model was a new pre-traint, which would lead us to believe that it would be a GPT6, but who knows? Maybe we'll see a GPD 5-7 Astra or maybe we'll see a GPD 5-6 Astra, but most reports are saying it could come as soon as next month. All right,

Starting point is 00:32:57 we actually have a ton under the what's new and what's next. So these are some smaller stories, some rumors, but we have a lot to get to. I'm going through them super quick. So buckle up because it was a wild week in AI. All right. So, InVedia partnered with SSI, that's safe superintelligence and a deal reportedly worth $5 billion. All right.

Starting point is 00:33:24 President Trump is considering AI controls after Sam Altman briefed senators. Google released Gemini Robotics ER2 in public preview. AWS posted a 37% growth as Amazon raised AI era capital. spending to $220 billion. A Reuters report said the Chinese military researchers used open AI and anthropic outputs to train defense systems. Yeah, distillation continues to be a problem. And now as part of national security,

Starting point is 00:33:57 meta and Black Rock created a $14 billion Al Paso data center venture. Anthropics MCP released a new update, a production focus update, adding stateless core, Tasks app in Enterprise authentication. Deep Seek, pretty big release with their V4 Flash that just came out in public beta. Looks like fairly impressive benchmarks, but the real impressive thing is the cost. It is crazy cheap. So another not good news for Anthropic.

Starting point is 00:34:31 The White House missed its self-imposed August 1st, executive order deadline for Frontier Oversight. Well, presumably they did unless they just. and released it Saturday and no one in the public knew. But, hey, when we checked Saturday, nothing was out. So we'll see if they release anything today. All right. So Open AI started rolling out. It's sign in with chat GPT to certain providers where you can sign into other websites

Starting point is 00:34:55 with your chat chbt credentials. Anthropic reported that Claude Mythos preview found weaknesses in experimental cryptographic systems. Yeah. So lock up your Bitcoin wallets apparently. All right. The FCC blocks new foreign-produced advanced robots from US. The Kimi K3 OpenWaets went live this past week.

Starting point is 00:35:17 Amazon reportedly completed its $50 billion open AI investment. Microsoft announced Project Perception, and it's extremely impressive MAI Cyber One Flash, which dusts away all other models, including Mythos 5 on cybersecurity. Quinn released a benchmark. for its Quinn 3.8 model, and they're pretty impressive. Google withdrew Google Earth AI image generator after one day, right?

Starting point is 00:35:49 That didn't go too well. They allowed anyone to use AI to kind of remake anything on Google Earth. And obviously, people did some pretty bad things. Microsoft 365 copilot passed $30 million paid seats. Meta's free cash flow fell 91% as AI infrastructure. structure spending rows. Chime cut 10% of its workforce, explicitly citing AI-driven efficiencies. InVIDIA leads the launch of the Open Secure AI Alliance.

Starting point is 00:36:21 We talked about that in our newsletter this past week. Open AI offered a free frontier tools to 100,000 academic researchers. So Open AI really trying to carve out its niche in scientific research. And then here's a quick bullet point. recap of everything we went over on Friday's show. We do new AI features you can actually use. So here's the ones we went over. Replit launched Replit design in AI Creative Suite.

Starting point is 00:36:49 The Chad ChbD Chrome extension got updated with YouTube Q&A, tab mentions, and highlighted tech support. MetaI introduced recurring tasks and daily briefings, powered by Muse Spark 1.1. Google Docs added Gemini image, diagram, infographics, and comment managed, Gemini tools. So yeah, you can do a lot more AI goodies inside of Google Docs. I'm happy for that one. Google also brought its Gemini Spark browser agent into Chrome for WebTas. So it's not just within Gemini anymore.

Starting point is 00:37:22 Google also released Lyria 3.5. It's updated AI music generation model inside of flow music. I actually thought it was really good. The lyrics were nonsensical. But if you just bring in your own lyrics or have Gemini or Claude or OpenAI, write the lyrics for, you. It's actually pretty good. I was impressed by the quality. And then last but not at least, another thing I've been fairly impressed with is the new open source tool launched by Block, former Twitter owner, Jack Dorsey. Block launched Buzz in open source Slack like workspace where essentially you're just working with your agents. So if you have, you know, codex and cloud code installed on your machine and cursor, they can all just talk to each other and work amongst themselves. That was a lot of AI news. This week,

Starting point is 00:38:08 some big, scary, but also very exciting developments in the world of AI. So I'm telling you, if you take, I actually got an email from someone recently, right, after taking like a two-week vacation. And they're like, I feel like I'm like months behind. But I'll tell you this, don't spend hours every single day, right, trying to keep up with this. That's why our newsletter takes about seven minutes to read. Usually our podcasts are about 30 minutes, right?

Starting point is 00:38:35 Don't spend hours doing this every day and worrying about it. talking about it. No, let us do the work for you. You go do your real work. We work for you. So just steal all our hard work. There you go. So hope this is helpful. If so, if you're listening on the podcast, do me a favor. Please subscribe on Spotify or Apple Podcasts. And then go to Your EverydayaI.com. Sign up for the free daily newsletter. We'll see you tomorrow and Every Day for more Everyday AI. Thanks y'all. And that's a wrap for today's edition of Everyday AI. Thanks for joining us. enjoyed this episode, please subscribe and leave us a rating. It helps keep us going. For a little more

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Everyday AI Podcast – An AI and ChatGPT Podcast - Ep 832: OpenAI’s new Astra model, more AI agents escape sandboxes, AI leaders call for AI pacing and more.

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